Data Driven Discovery of Topological Phononic Materials

This DMREF project has demonstrated an alternative avenue for the prediction of new topological materials from simple spectroscopic features, addressing the DMREF value of “significantly accelerate materials discovery and development”. In particular, the synergy of machine-learning modeling with the experimental validation addresses the DMREF concept to “work synergistically in a closed loop fashion.” The broadening of materials candidates further supports the DMREF mission to foster the “translation of materials research toward application”.

This  DMREF  project  has  demonstrated  an alternative  avenue  for  the  prediction  of  new topological  materials  from  simple  spectroscopic features,   addressing   the   DMREF   value   of “significantly  accelerate  materials  discovery  and development”. In particular, the synergy of machine-learning  modeling  with  the  experimental  validation addresses   the   DMREF   concept   to   “work synergistically  in  a  closed  loop  fashion.”  The broadening  of  materials  candidates  further  supports the  DMREF  mission  to  foster  the  “translation  of materials research toward application”.

Designing Materials to Revolutionize and Engineer our Future (DMREF)